Data Engineer - DBT, Snowflake, Power BI, ADF

Data Engineer - DBT, Snowflake, Power BI, ADF
Spring, TX - Onsite
Dexian/Exxon

Here is the Overview of the mechanics of the role:

Overview
Your data models show leaders how their projects perform. In this role, you own the analytics layer that turns raw data into trusted star schemas in Snowflake, built with dbt (data build tool) and used in Power BI. You spend about 70% of your time hands-on and the rest reviewing code, coaching engineers, and bringing in new ideas. You don t need industry-specific experience. Strong data engineering practice is what counts.

Responsibilities

• Design and build star-schema data models in Snowflake using dbt, including fact, dimension, bridge, and aggregate tables.
• Own the data flow end to end, from intake in Azure Data Factory (ADF), through dbt and a Data Vault layer, to the star schemas that power Power BI reports.
• Write, tune, and automate complex SQL and large Snowflake workloads.
• Build dbt tests, documentation, and reusable patterns that keep data quality high.
• Automate builds and infrastructure with GitHub Actions and Terraform.
• Review code, spot what works and what doesn t, and coach backend developers and data engineers side by side.
• Set data modeling standards and shape architecture decisions for the platform.
• Propose improvements and bring new ideas to the platform.
• Support the API components that feed data into the platform.
• Partner with product owners, architects, and business teams to turn project performance questions into data models.

Qualifications

Required

• 8+ years in data engineering or data warehousing, including 4+ years of hands-on dbt and Snowflake work.
• Expert, hands-on dbt experience: you ve built models, written tests, and deployed them to production yourself.
• Expert Snowflake experience, including architecture, performance tuning, and SQL optimization.
• Proven work designing and building enterprise-scale star-schema (dimensional) data models.
• Hands-on experience automating SQL workloads and data processes.
• A track record of working on your own, solving data problems from start to finish, and leading technical design decisions.
• Hands-on experience with GitHub for version control and team development.

Preferred

• Data Vault modeling.
• Azure Data Factory (ADF), Azure Synapse, or Microsoft Fabric.
• GitHub Actions and Terraform.
• Python for data engineering and automation.
• Experience using AI in data work.
• Experience with API data integration.
• Observability tools such as Datadog.
• SnowPro, DP-203, or similar cloud data certifications.